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Category: Semantic technologies (Page 4 of 72)

Our coverage of semantic technologies goes back to the early 90s when search engines focused on searching structured data in databases were looking to provide support for searching unstructured or semi-structured data. This early Gilbane Report, Document Query Languages – Why is it so Hard to Ask a Simple Question?, analyses the challenge back then.

Semantic technology is a broad topic that includes all natural language processing, as well as the semantic web, linked data processing, and knowledge graphs.

Access Innovations and Aptara partner to provide digital publishing solutions

November 7, 2022 /

Access Innovations, Inc., provider of Data Harmony software solutions, announced a partnership with Aptara to provide intelligent publishing solutions to book and journal publishers. Serving as a digital publishing provider since 1988, Aptara is proficient in designing and developing custom content for Fortune 500 companies and other organizations from all industries. They create, enrich, and optimize content to ensure it can be reused and repurposed — future-proofing it for all known and as yet undiscovered outputs.

Both Aptara and Access Innovations have extensive content experience, from structuring to conversion and metadata enrichment. Having the depth of experience will provide the combined client base with a full range of services to help reduce expenses while creating the digital-first experience most publishers need to compete in today’s evolving publishing industry. With this partnership in place Aptara clients can expect to see smoothly integrated options for taxonomies, and other metadata enhancement offered as a regular production flow service. Access Innovations clients can utilize significant additional options in production and distribution options.

https://www.accessinn.com ■ https://www.aptaracorp.com

Pinecone launches hybrid search functionality

October 31, 2022 /

Pinecone Systems Inc., a machine learning (ML) search infrastructure company, announced the release of a keyword-aware semantic search solution that enables accessible and advanced combination of semantic and keyword search results. “Vector search” allows companies to provide relevant results based on semantic, or similar meanings, as opposed to simple keyword-based searches. At the same time, keywords still matter in searches involving uncommon words like names or industry-specific terms. With few exceptions, companies have to choose between semantic search and keyword search, or running both systems in parallel.

Neither of these options is ideal. When companies choose one or the other, the results are not as complete as they could be, and when they run both systems in parallel and try to combine the results, cost and complexity goes up significantly. This technology can search across two data types — “dense vectors” generated by ML models to represent meaning, and “sparse vectors” generated by traditional keyword-ranking models such as BM25 — before automatically fusing everything into one ranked list of the most relevant results. The Pinecone hybrid search feature is available in beta.

https://www.pinecone.io/hybrid-search-early-access

AtScale adds enterprise AI capabilities to semantic layer platform 

September 28, 2022 /

AtScale, a provider of semantic layer solutions for modern business intelligence and data science teams, announced new product capabilities for organizations working to accelerate the deployment of enterprise artificial intelligence (AI). These new capabilities leverage AtScale’s position within the data stack with cloud data warehouse and lakehouse platforms including Google BigQuery, Microsoft Azure Synapse, Amazon Redshift, Snowflake, and Databricks. The AtScale Enterprise semantic layer platform now incorporates:

  • Semantic Predictions – Predictions generated by deployed AI/ML models can be written back to cloud data platforms through AtScale. These model-generated predictive statistics inherit semantic model intelligence, including dimensional consistency and discoverability. Predictions are immediately available for exploration by business users using BI tools (AtScale supports connectivity to Looker, PowerBI, Tableau, and Excel) and can be incorporated into augmented analytics resources.
  • Managed Features – AtScale creates a hub of centrally governed metrics and dimensional hierarchies that can be used to create a set of managed features for AI/ML models. AtScale managed features inherit semantic context, making them more discoverable and easier to work with. Managed features can now be served directly from AtScale, or through a feature store like FEAST, to train models in AutoML or other AI platforms.

https://www.atscale.com/product/ai-link/

Apptek and expert.ai announce strategic partnership

September 26, 2022 /

AppTek and expert.ai announced they have entered into a strategic technology partnership to bring AI-based text analytics to dynamic audio content in multiple languages. The partnership leverages AppTek’s Automatic Speech Recognition (ASR) and Neural Machine Translation (NMT) technologies with expert.ai’s natural language understanding capabilities to enable organizations to leverage audio content in the unstructured data sets that they manage for improving decision making and augmenting intelligent automation.

As organizations increasingly utilize language data—emails, documents, reports and other free form text— for an ever-growing range of enterprise use cases (knowledge discovery, contract analysis, policy review, email management, text summarization, classification, entity extraction etc.), natural language capabilities will play a critical role in powering any process or application that relies on unstructured language data. The combined capabilities of AppTek and expert.ai supercharge enterprise and government NLU and NLP applications, expanding the data types and sources available for analysis to provide even more informational output.

Using AppTek’s speech-to-text technology within the expert.ai Platform, organizations can automatically transcribe audio types from different sources, including high-quality media broadcast content, podcasts, meetings, one-to-one interviews or even low bandwidth telephone conversations. In addition, they can leverage advanced multilingual functionalities to generate accurate, customizable and scalable translations across hundreds of language pairs.

https://www.apptek.com/ ■ https://www.expert.ai/

Stardog joins Databricks Partner Connect

September 23, 2022 /

Stardog, an Enterprise Knowledge Graph platform provider, today announced it had joined Databricks Partner Connect, which lets Databricks customers integrate with select partners directly from within their Databricks workspace. Stardog is the first Databricks partner to deliver a knowledge-graph-powered semantic layer. Now with just a few clicks, data analysts, data engineers, and data scientists can model, explore, access, and infer new insights for analytics, AI, and data fabric needs — an end-to-end user experience without the burden of moving or copying data. Together, Stardog’s availability on Databricks Partner Connect enables joint customers to:

  • Easily define and reuse relevant business concepts and relationships as a semantic data model meaningful to multiple use cases.
  • Link and query data in and outside of the Databricks Lakehouse Platform to provide just-in-time cross-domain analytics for richer insights.
  • Ask and answer questions across a diverse set of connected data domains to fuel new business insights without the need for specialized skills.

https://www.stardog.com ■ https://www.databricks.com/partnerconnect

Algolia acquires Search.io

September 12, 2022 /

Algolia, an API-First Search & Discovery Platform, announced the acquisition of Search.io, whose flagship product is Neuralsearch – a vector search engine that uses hashing technology on top of vectors to provide price performance at scale. Algolia will combine its keyword search and Search.io’s Neuralsearch into a single API-First Search and Discovery platform with a hybrid search engine, which comprises both keyword and semantic search in a single API.

The combination of Algolia (with its keyword search) and Search.io (with its vector-based semantic search), enables Algolia to more effectively surface the most accurate and relevant results for users, whether they use specific keywords or natural human expressions. Many companies claim to offer some form of semantic search, however, these companies may not offer the capabilities of keyword search and vector-based semantic search in a single API cost-effectively, or the ability to scale. In essence, Algolia provides users with the ability to search as they think. With Search.io, Algolia aims to empower business users with a better way to manage the automation of unique and engaging end user experiences.

https://www.algolia.com/about/news/algolia-disrupts-market-with-search-io-acquisition-ushering-in-a-new-era-of-search-and-discovery/

Ontotext announces Metadata Studio

September 8, 2022 /

Ontotext introduced Ontotext Metadata Studio, built on top of the GraphDB and Ontotext Platform. Metadata Studio enables organizations to get more out of their content by unlocking new business models or achieving cost optimizations by putting their own Subject Matter Experts (SME) at the heart of text analysis.

With Ontotext Metadata Studio, organizations can use business analysts to define Semantic Objects as specific views, abstracting developers away from the complexity and peculiarities of the knowledge graph. This allows them to reference the pre-existing domain knowledge modeled in their ontologies and annotate relevant documents following the established Annotation Guidelines for the specific use case.

Ontotext Metadata Studio can be integrated with many text analysis services via GraphDB’s Text Mining Plugin, e.g., spaCy, IBM Watson, Amazon Comprehend, Google NLP, Ontotext Tag (powering the Ontotext NOW demonstrator), etc. This enables the evaluation of a service or the suitability of a combination of services for the currently explored use case against the ground truth data produced by the annotators. This can shorten the Time to market (TTM) for new product development.

https://www.ontotext.com/products/ontotext-metadata-studio/

Data Harmony suite Recommender released

July 19, 2022 /

Access Innovations, Inc., provider of Data Harmony software solutions, announced the release of their new Recommender as part of the Data Harmony Suite. Recommender is now available to all Data Harmony clients using versions 3.16 or higher.

Recommender uses the semantic fingerprint of an article, its subject metadata tagging, matching to other articles and content within the database. When the searcher finds an article they like, the Recommender automatically displays other items with the same semantic fingerprint nearby on the search interface. This allows immediate display of highly relevant content to the search without scrolling and frustration in trying to find similar items. It also allows for display of other relevant content such as conference papers, ads, books, meetings, expert profiles, and so forth.

This is not based on personalization profiles or purchasing history. By using the metadata weighting and other algorithms it provides only items relevant to the current query faster search and the surfacing of more related information to the user.

For those interested in using Recommender there are two prerequisites: 1) the content needs to be indexed or tagged using a controlled vocabulary like a thesaurus or taxonomy, and 2) the search interface needs to be able to accommodate the API call to the tagged data and subsequent display of the results.

https://www.accessinn.com

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